A novel attribute weighting method with genetic algorithm for document classification

S. Ay, Yavuz Selim Dogan, Seyfullah Alver, Cetin Kaya
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引用次数: 2

Abstract

Thanks to the proliferation of Internet, a lot of data are produced by both Web sites and personal users. The documents are required to be classified in terms of their content in order to reach the necessary information fast and correctly from produced data. One of the biggest difficulties in document classification systems is detection of attribute that represent the classes in best way. In this research, a new attribute method is presented by using a Genetic Algorithm for document classification problem. This proposed method is tested on 450 documents that are from 6 different categories collected from a news portal that broadcasts online. According to experimental results 93% of success is achieved with the proposed method.
一种基于遗传算法的属性加权方法用于文档分类
由于互联网的普及,大量的数据是由网站和个人用户产生的。这些文件需要根据其内容进行分类,以便从生成的数据中快速正确地获得必要的信息。文档分类系统中最大的困难之一是检测以最佳方式表示类的属性。本文提出了一种基于遗传算法的属性分类方法。该方法在从在线广播的新闻门户网站收集的6个不同类别的450个文档上进行了测试。实验结果表明,该方法的成功率为93%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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